Senior Data Engineer

NVIDIA Corporation; Sacramento (CA); On-site; USD 168,000 - 270,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA's Digital Marketing Operations team in the United States is seeking a Senior Data Engineer to build the shared data infrastructure powering customer engagement, campaign intelligence, and marketing analytics at scale.

You will own a data domain, lead cross-functional initiatives, and collaborate across teams to translate requirements into robust data architectures while building batch and streaming pipelines with Spark and Airflow on a cloud data platform.

Qualifications

• 8+ years of relevant industry experience with a Bachelor's or equivalent experience, and a Master's degree or equivalent in CS, Engineering, or related field.
• Proficiency in Python and Java or Golang with strong SQL fundamentals and production-quality code.
• Experience with distributed data processing frameworks (e.g., Apache Spark) and cloud ETL services.
• Experience with Airflow or similar workflow orchestration tools.
• Experience with cloud data platform services and large-scale data workflows.
• Experience with data lake/lakehouse architectures and Open Table formats like Iceberg.
• Strong data modeling, governance, and reliability focus.
• Ability to diagnose production failures across distributed systems and implement durable fixes.

Responsibilities

• Own a key data domain within Digital Marketing Operations and shape its architecture for scale, reliability, privacy, and cost.
• Lead complex, cross-functional initiatives across engineering, marketing, and operations.
• Translate requirements into data architectures, write high-quality production code, and drive safe production integrations.
• Architect and evolve batch and streaming pipelines ingesting customer behavioral, audience, campaign, consent, and activation data.
• Build data quality frameworks and engineering standards to improve reliability and efficiency.
• Lead incident investigations and drive root-cause analysis and preventive improvements.
• Embed privacy and compliance by design with data governance and lineage requirements.
• Deliver trusted data assets with accessible interfaces for marketing consumers while maintaining accuracy and privacy.
• Provide technical leadership through architecture reviews and mentorship.
• Raise engineering quality with reusable patterns and clear decisions.

Skills

Python

Java

Golang

SQL

Spark

Airflow

Distributed data processing

Cloud data platforms

Education

Bachelor's degree or equivalent in CS/Engineering

Master's degree or equivalent in CS/Engineering

Tools

Apache Spark

Airflow

Iceberg/open table formats

Cloud data warehouses

Job description

NVIDIA's Digital Marketing Operations team is seeking a Senior Data Engineer to help build the shared data infrastructure that powers customer engagement, campaign intelligence, and marketing analytics at scale. Our data platform transforms customer behavioral signals, audience definitions, consent records, campaign metadata, and activation outputs into trusted, governed data products for marketing, analytics, personalization, campaign operations, and regional teams worldwide. These products enable audience segmentation, campaign performance measurement, privacy-compliant data activation, identity resolution, and the continued growth of NVIDIA's marketing technology ecosystem.

What You'll Be Doing:

• Own a key data domain within Digital Marketing Operations, spanning pipelines, data products, audience services, and consumer teams. Shape its architecture and interfaces while anticipating needs related to scale, reliability, performance, privacy compliance, security, cost, and compatibility.
• Lead complex, cross-functional initiatives.
• Collaborate across engineering, marketing, and operations stakeholders to translate requirements into clear data architectures, write high-quality code in the critical path, and drive integrations safely into production.
• Architect, implement, and evolve batch and streaming pipelines that ingest, transform, reconcile, and serve customer behavioral, audience, campaign, consent, and activation data at scale. Build reliable, maintainable systems leveraging distributed processing frameworks, workflow orchestration tools, cloud data warehouses, object storage, and pub/sub messaging platforms.
• Build and evolve shared data quality frameworks and engineering standards that improve pipeline reliability, consistency, and efficiency across teams.
• Lead production incident investigations across pipelines, distributed processing, storage, and cloud services. Coordinate across system owners to establish root cause, drive resolution, and implement preventive improvements.
• Embed privacy and compliance by design across the data platform. Implement and enforce data governance, consent propagation, GDPR and PIPL compliance controls, data minimization, access boundaries, right-to-erasure workflows, and auditable data lineage as first-class engineering requirements, not afterthoughts.
• Establish robust data models, semantics, ownership boundaries, and serving interfaces across teams. Deliver trusted data assets that make customer and campaign data widely accessible to marketing consumers without sacrificing accuracy, privacy, or maintainability.
• Provide technical leadership through architecture and data model reviews, hands-on mentorship of junior engineers, and evidence-based resolution of difficult tradeoffs.
• Raise engineering quality across teams through reusable patterns, clear decisions, and sustained follow-through.

What We Need To See:

• 8+ years of relevant industry experience with a Bachelor's or equivalent experience, and a Master's degree or equivalent in Computer Science, Engineering, or a related field.
• A sustained record of designing, implementing, and operating production data pipelines, data platforms, or distributed data systems. This includes end-to-end technical ownership of a multi-pipeline domain or a complex cross-team data engineering initiative.
• Proficiency in Python and one or more modern programming languages such as Java or Golang, with strong SQL fundamentals and the ability to write clean, testable, production-quality code.
• Deep hands-on experience with distributed data processing frameworks such as Apache Spark, and cloud-managed ETL services. Experience building and operating production pipelines with workflow orchestration tools such as Airflow or equivalent.
• Strong experience with cloud data platform services, including object storage, cloud data warehouses, managed transformation services, and related infrastructure. Demonstrated ability to architect and operate large-scale data workflows in a cloud environment.
• Experience with data lake and lakehouse architectures, including open table formats such as Apache Iceberg. Ability to design, manage, and optimize large-scale data storage for reliable analytical consumption.
• Strong SQL and NoSQL skills and data-modeling proficiency, including practical depth in query execution, incremental processing, schema evolution, consistency, analytical consumption patterns, idempotency, replay, late-arriving data, partial failure, and cross-system correctness.
• Experience building systems that move customer, behavioral, consent, campaign, or audience data across multiple platforms, with strong attention to data quality, governance, and operational reliability.
• Demonstrated skill in diagnosing production failures across distributed systems by analyzing logs, metrics, traces, query plans, and profiles, followed by implementing and validating long-lasting resolutions.
• Strong architectural judgment in assessing tradeoffs among reliability, performance, cost, privacy, compatibility, and maintainability. Experience guiding major migrations or architectural changes across teams without interrupting production service.

Ways To Stand Out From The Crowd:

• Experience with MarTech stacks and B2C customer data at scale, including CDP integrations, reverse ETL, identity resolution, customer 360 or profile services, audience activation pipelines, campaign metadata, tracking code management, and multi-touch attribution.
• Experience designing and operating high-throughput, fault-tolerant streaming systems at scale, including exactly-once delivery semantics, consumer lag management, schema registry patterns, and replay strategies for large data volumes.

NVIDIA is widely considered to be one of the technology world's most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 270,250 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 23, 2026.

This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.